handwritten information out of them and converting it into a digital format without human intervention reduces manual errors, lowers cost, allows big data analytics and makes turn around considerably faster.

The speed of this AI-based processing is impressive. Anywhere up to 50,000 pages per hour can be completed using a single server – with bigger deployments and cloud delivery also possible when more compute power is added.

Loads of different common files can be ingested for analysis such as plain text, PDF, TIFF, JPEG, GIF, PPM, PNG and so on with several neural nets then reading the text and classifying the type – whether it be handwriting or machine print – with ‘fuzzy search’ aiding the text to digital conversion process. And, class-leading AI systems - in addition to handling paper documents - are designed to cope with pictures, video and audio, too. Put another way, they are content agnostic and can handle any source content.

AI in practice This is real stuff. One German insurance firm is working over the next six years to shift its entire claim process to use an AI-powered system such that claims under a certain value will be handled automatically based on information extracted, assessed and approved from a form with no human involvement required at all. This will be accomplished as the AI solution automatically checks the name, address, insurance number and other key details about a given incident – capturing all the data from the form correctly first time every time.

It’s not dissimilar to how the human brain works and children learn a language. In other words, the more kids talk, make mistakes and are corrected, the better they get at speaking. The same is true with AI when applied to document analysis and processing. The inference becomes ever more knowledgeable and accurate.

AI-based systems can be trained to automatically recognise specific forms, review specific content and its layout on the page and then convert cursive handwriting into standard electronic formats such as PDF or JSON for analysis or workflow purposes with validation and verification also taking place. This can also be done at a field-based level so that key value extraction can be completed. Admittedly this something that ICR/OCR systems can also do but they struggle to recognise cursive handwriting and require complex algorithms to find the fields.

Key value extraction on a form, for example, could be a generic box for ‘name’ or ‘age’ – the key – and then the specific values would be ‘Mr John Smith’ and ‘50’. Or on an invoice, the keys are items purchased and the values are the prices paid for each different one.

The benefits here are clear. Governments, healthcare providers, banks and insurance firms have to process a vast number of handwritten forms with identical formats for various purposes like questionnaires, applications, personal loans, mortgages or claims. Retrieving the

When it comes to document processing, seeing AI in action is impressive. It’s ‘wow’ magical stuff to watch a machine ‘read’ a scanned paper document and extract data from it.

“The speed of this AI-based processing is impressive.

Anywhere up to 50,000 pages

per hour can be completed using a single server.”

One of the consequences of the COVID-19 pandemic and the economic fallout from it is that many companies will want to improve efficiency in a bid to save money. Those who have a significant cost and operational overhead processing forms and other documentation many feel a sense of corporate anxiety or even alarm about how to do this.

As The Hitchhiker’s Guide helpfully advised on its cover, don’t panic. AI has sufficiently matured such that it is now a real- world performant and reliable option for companies tasked with grappling and dealing with millions of paper documents. TOMORROW’S FM | 33

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